Add to ORKGIn this video, Dr Gabriel Katz discusses methods that could enable researchers working within the Bayesian paradigm to speed up conversion or execution time of computations. These methods include c+++, cluster computing services or cloud computing
We are concerned primarily with improving the practical applicability of Bayesian optimization. We m...
Many applications in Bayesian statistics are extremely computationally intensive. However, they are ...
Challenging statements have appeared in recent years in the literature on advances in computational ...
In this video, Dr Gabriel Katz introduces this online resource which will explore fundamental aspect...
In this video, Dr Gabriel Katz talks about the basics of Bayesian computation, working through a ser...
In this video, Dr Gabriel Katz looks at the second main algorithm used in Bayesian computations, whi...
Current statistical methods for facilitating data-driven decision making are too computationally int...
In this video, Dr Gabriel Katz presents two key approaches to Bayesian simulation: the Gibbs sample...
© 2015, The Author(s). Recent decades have seen enormous improvements in computational inference for...
In this video, Associate Professor Gabriel explores convergence and how it can be assessed when esti...
The past decades have seen enormous im-provements in computational inference based on sta-tistical m...
Bayesian analysis offers a powerful tool for data analysis, as it is able to make probabilistic stat...
While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the curren...
Recent decades have seen enormous improvements in computational inference for statistical models; th...
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions o...
We are concerned primarily with improving the practical applicability of Bayesian optimization. We m...
Many applications in Bayesian statistics are extremely computationally intensive. However, they are ...
Challenging statements have appeared in recent years in the literature on advances in computational ...
In this video, Dr Gabriel Katz introduces this online resource which will explore fundamental aspect...
In this video, Dr Gabriel Katz talks about the basics of Bayesian computation, working through a ser...
In this video, Dr Gabriel Katz looks at the second main algorithm used in Bayesian computations, whi...
Current statistical methods for facilitating data-driven decision making are too computationally int...
In this video, Dr Gabriel Katz presents two key approaches to Bayesian simulation: the Gibbs sample...
© 2015, The Author(s). Recent decades have seen enormous improvements in computational inference for...
In this video, Associate Professor Gabriel explores convergence and how it can be assessed when esti...
The past decades have seen enormous im-provements in computational inference based on sta-tistical m...
Bayesian analysis offers a powerful tool for data analysis, as it is able to make probabilistic stat...
While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the curren...
Recent decades have seen enormous improvements in computational inference for statistical models; th...
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions o...
We are concerned primarily with improving the practical applicability of Bayesian optimization. We m...
Many applications in Bayesian statistics are extremely computationally intensive. However, they are ...
Challenging statements have appeared in recent years in the literature on advances in computational ...